Senior Software Engineer - AIML

Kaleris; Chennai District; On-site; INR 1,500,000 - 2,000,000; Full time

Benefits offered by this job

Competitive salary

Inclusive culture

Opportunities for growth

Job summary

A leading technology firm in Chennai is seeking a Senior AIML Software Engineer to drive scalable ML/RL solutions within global supply chains. This role involves architecting end-to-end platforms, ensuring data quality, optimizing production workflows, and mentoring engineers. The ideal candidate holds an advanced degree in Computer Science and has 5–8 years of experience with ML systems, proficiency in Python and deep learning frameworks, and familiarity with cloud platforms such as Azure, AWS, or GCP. The position offers competitive salary and benefits.

Qualifications

• 5–8+ years building and operating ML systems in production.
• Expert-level experience with machine learning model development and evaluation.
• Hands-on experience with monitoring and incident response for ML services.

Responsibilities

• Architect end-to-end ML/RL platforms for various applications.
• Optimize production workflows for performance and security.
• Mentor and coach engineers and data scientists.

Skills

Python

Deep learning frameworks (PyTorch or TensorFlow)

scikit-learn

pandas

numpy

Docker

Kubernetes

CI/CD

Education

Bachelor’s/Master’s/PhD in Computer Science or related field

Tools

Azure

AWS

GCP

Monitoring tools

Job description

About Kaleris and the Role

Lead the architecture and delivery of scalable ML/RL systems at Kaleris. As a Senior AIML Software Engineer, you’ll set technical standards, mentor engineers, and drive initiatives from problem framing through production operations, shaping AI solutions that materially improve throughput, cost, and service reliability for global supply chains.

Job Description

What You’ll Do

• Architect end-to-end ML/RL platforms: pipelines, training/evaluation environments, model serving, monitoring, and incident response.
• Establish data quality standards, observability, and governance across ML products.
• Optimize production workflows for performance, latency, scalability, and security.
• Lead technical reviews, elevate code/design quality, and ensure reproducible experimentation.
• Partner cross-functionally to translate business goals into model objectives, success metrics, and deployment strategies.
• Mentor and coach engineers and data scientists; promote best practices and continuous improvement.

Minimum Qualifications

• Bachelor’s/Master’s/PhD in Computer Science or related field; 5–8+ years building and operating ML systems in production.
• Advanced proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
• Expert‑level experience with scikit‑learn, pandas, numpy, and machine learning model development and evaluation.
• Proven track record deploying on Azure/AWS/GCP; strong with Docker, Kubernetes, and CI/CD.
• Hands‑on experience with monitoring, drift detection, alerting, and incident response for ML services.

Preferred Qualifications

• Simulation expertise (discrete‑event or agent‑based), queueing/stochastic modeling, and reinforcement learning in real‑world settings.
• MLOps depth: model versioning, experiment tracking, automated retraining, governance.
• Logistics/supply chain domain experience and optimization in complex/partially observable environments.
• Experience with serverless functions and event-driven architectures for low-latency model APIs, including Knative, Azure Functions, and AWS Lambda.

Why Kaleris

• Own strategic ML initiatives with direct line‑of‑sight to customer impact.
• Influence product direction and technical standards in a modern AI/ML organization.
• Competitive salary and benefits; inclusive culture; opportunities to grow scope and leadership.

Kaleris is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.